Research on the impact of policy tool combinations on digital technology R&D alliances in complex network environments
摘要
Policy tools serve as critical instruments for promoting the diffusion of digital technology R&D alliances. However, there remains a lack of in-depth analysis regarding the combined effects and dynamic revenue of these policy tools. Based on the complex network evolution game model, this study systematically investigates the comprehensive impact of various policy tool combinations on digital technology R&D alliances, innovatively integrating the rule-based context of the dynamic revenue mechanism. The findings reveal that individual policies can all play positive roles in fostering digital technology R&D alliances. Nevertheless, the combined effects of policy tools vary, leading to heterogeneous outcomes such as enhancement, weakening, or even reversal. Under the dynamic revenue mechanism, factors such as innovation dividend factor, opportunity loss factor and revenue influence cycle exhibit positive promoting effects. Conversely, the scale of the network may exert adverse effects when it becomes excessively large. This research broadens the analytical perspective of digital technology R&D alliances by considering the combination of policy tools and the dynamic revenue mechanism, thereby proposing corresponding strategies that can provide optimization insights for both enterprise alliance strategies and government management mechanisms in the realm of digital technology R&D.